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Updated: Aug 2, 2025
Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification
Published on: November 28, 2016
Potential Novel RNA-Targeting Agents for Effective Lipoprotein(a) Lowering: A Systematic Assessment of the Evidence
Milos N Milosavljevic1, Srdjan M Stefanovic2,3, Ana V Pejcic1
1Department of Pharmacology and Toxicology, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia.
Abstract:
An increase in blood lipoprotein (a) [Lp(a)] levels, mostly genetically determined, has been identified as an independent risk factor of atherosclerotic cardiovascular disease. No drug has yet been approved that markedly lowers Lp(a) and thereby reduces residual cardiovascular risk. The aim of this article was to critically review the evidence from clinical development studies to date on the efficacy and safety of new RNA-based therapeutics for targeted lowering of Lp(a). PubMed/MEDLINE, Scopus, Web of Science, and ClinicalTrials.gov were searched without any language or date restriction up to November 5, 2022, and a total of 12 publications and 22 trial records were included. Several drugs were found that are currently in various stages of clinical development, such as the antisense oligonucleotide pelacarsen and the small interfering RNA molecule olpasiran and drugs coded as SLN360 and LY3819469. Among them, pelacarsen has progressed the most, currently reaching phase 3. All these drugs have so far shown satisfactory pharmacokinetic properties, consistently high and stable, dose-dependent efficacy in lowering Lp(a) even by more than 90%, with an acceptable safety profile in subjects with highly elevated Lp(a). In addition, reports of early clinical trials with pelacarsen imply a promising suppressive effect on key mechanisms of atherogenesis. Future research should focus on confirming these beneficial clinical effects in patients with lower average Lp(a) levels and clearly demonstrating the association between lowering Lp(a) and reducing adverse cardiovascular outcomes.
Insights
New RNA-based therapies show promise in significantly lowering lipoprotein (a) [Lp(a)] levels, a key risk factor for cardiovascular disease. These treatments demonstrate high efficacy and safety, offering hope for reducing residual cardiovascular risk.
Area of Science:
- Cardiovascular Medicine
- Pharmacology
- Genetics
Background:
- Elevated lipoprotein (a) [Lp(a)] is a genetically determined, independent risk factor for atherosclerotic cardiovascular disease.
- Current therapeutic options for markedly reducing Lp(a) and residual cardiovascular risk are limited.
- RNA-based therapeutics offer a novel approach to target Lp(a) lowering.
Purpose of the Study:
- To critically review clinical development studies on the efficacy and safety of RNA-based therapeutics for targeted Lp(a) lowering.
- To assess the current progress and potential of these novel treatments in managing cardiovascular risk.
- To identify future research directions for Lp(a)-lowering therapies.
Main Methods:
- Comprehensive literature search of PubMed/MEDLINE, Scopus, Web of Science, and ClinicalTrials.gov up to November 5, 2022.
- Inclusion of 12 publications and 22 trial records detailing RNA-based Lp(a)-lowering drug development.
- Focus on efficacy, safety, pharmacokinetic properties, and clinical effects of investigational drugs.
Main Results:
- Several RNA-based drugs, including pelacarsen, olpasiran, SLN360, and LY3819469, are in clinical development.
- Pelacarsen has advanced to Phase 3 trials.
- These agents demonstrate dose-dependent Lp(a) reduction exceeding 90% with favorable pharmacokinetics and safety profiles.
- Early data suggest pelacarsen may suppress key atherogenesis mechanisms.
Conclusions:
- RNA-based therapeutics show significant potential for effectively and safely lowering Lp(a) in individuals with highly elevated levels.
- Pelacarsen is the most advanced in clinical development, with promising early findings.
- Further research is needed to confirm clinical benefits and cardiovascular outcome reductions in broader patient populations.
